Pickl AI

APRIL 27, 2023

Read Blog: W hich technologies combine to make data a critical organizational asset? Python Might Go Viral Yes, you read it right. While several programming languages play a significant role across different technologies, Python holds a special position. Add to this, Python has a friendly learning curve for beginners.

Data Science 52

Data Science Artificial Intelligence Artificial Intelligence Python 52

Viso.ai

SEPTEMBER 2, 2024

Experience with classical computer vision tools, such as OpenCV , object detection, image segmentation, data annotation, etc. Proficiency with one or more programming languages such as Python or C++, and tools like TensorFlow, and PyTorch. Verifying and validating annotations to maintain high data quality and reliability.

Computer Vision 52

Computer Vision Software Engineer Convolutional Neural Networks Neural Network 52

AWS Machine Learning Blog

FEBRUARY 28, 2023

If you want to add rules to monitor your data pipeline’s quality over time, you can add a step for AWS Glue Data Quality. And if you want to add more bespoke integrations, Step Functions lets you scale out to handle as much data or as little data as you need in parallel and only pay for what you use.

ML 81

ML Machine Learning Categorization NLP 81

The MLOps Blog

AUGUST 3, 2023

You essentially divide things up into large tasks and chunks, but the software engineering that goes within that task is the thing that you’re generally gonna be updating and adding to over time as your machine learning grows within your company or you have new data sources, you want to create new models, right? To figure it out.

ML 52

ML Data Scientist Software Engineer Machine Learning 52

The MLOps Blog

APRIL 17, 2023

Robustness You need an elastic data model to support: Varying team sizes and structures (a single data scientist only, or maybe a team of one data scientist, 4 machine learning engineers, 2 DevOps engineers, etc.). Varying workflows so users can decide what they want to track. Some will only track the post-training phase.

Metadata 52

Metadata Data Scientist Explainability ML 52

The MLOps Blog

MAY 9, 2023

The components comprise implementations of the manual workflow process you engage in for automatable steps, including: Data ingestion (extraction and versioning). Data validation (writing tests to check for data quality). Data preprocessing. Model performance analysis and evaluation.

ML 98

ML Machine Learning Metadata Data Science 98

The MLOps Blog

MARCH 21, 2023

” — Isaac Vidas , Shopify’s ML Platform Lead, at Ray Summit 2022 Monitoring Monitoring is an essential DevOps practice, and MLOps should be no different. Collaboration The principles you have learned in this guide are mostly born out of DevOps principles. My Story DevOps Engineers Who they are?

Machine Learning 69

Machine Learning Data Scientist ML Metadata 69

Pickl AI

MAY 15, 2024

Data Quality and Standardization The adage “garbage in, garbage out” holds true. Inconsistent data formats, missing values, and data bias can significantly impact the success of large-scale Data Science projects. This builds trust in model results and enables debugging or bias mitigation strategies.

Data Scientist 52

Data Scientist Data Science Machine Learning Data Quality 52